The ability to directly identify mould spores or pollen through air measurement tools is limited, as distinguishing these biological particles from other airborne matter like dust poses significant challenges. Currently, assessments are confined to identifying environmental conditions conducive to mould growth, notably high moisture levels and inadequate ventilation. However, novel approaches involves enhancing sensor technology and leveraging artificial intelligence (AI) to precisely classify particles by their characteristics, such as type and size. The integration of AI promises to transform the analysis of voluminous data collected from diverse sensors and sources, employing machine learning and advanced analytics to uncover intricate patterns and relationships within air quality data. Through these innovations is to significantly improve the precision, speed, and reliability of air pollutant detection, ushering in a new era of environmental monitoring.
Mould and Pollen